End of training
Browse files- README.md +2 -2
- checkpoint-100/custom_checkpoint_0.pkl +1 -1
- checkpoint-100/optimizer.bin +1 -1
- checkpoint-100/pytorch_model.bin +1 -1
- checkpoint-200/custom_checkpoint_0.pkl +1 -1
- checkpoint-200/optimizer.bin +1 -1
- checkpoint-200/pytorch_model.bin +1 -1
- checkpoint-300/custom_checkpoint_0.pkl +1 -1
- checkpoint-300/optimizer.bin +1 -1
- checkpoint-300/pytorch_model.bin +1 -1
- checkpoint-400/custom_checkpoint_0.pkl +1 -1
- checkpoint-400/optimizer.bin +1 -1
- checkpoint-400/pytorch_model.bin +1 -1
- checkpoint-500/custom_checkpoint_0.pkl +1 -1
- checkpoint-500/optimizer.bin +1 -1
- checkpoint-500/pytorch_model.bin +1 -1
- image_0.png +0 -0
- image_1.png +0 -0
- image_2.png +0 -0
- image_3.png +0 -0
- pytorch_lora_weights.bin +1 -1
README.md
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---
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license: creativeml-openrail-m
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base_model: /home/ubuntu/model/stable-diffusion-v1-4
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instance_prompt: a
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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---
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# LoRA DreamBooth - heine123/emoji_out
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These are LoRA adaption weights for /home/ubuntu/model/stable-diffusion-v1-4. The weights were trained on a
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![img_0](./image_0.png)
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![img_1](./image_1.png)
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---
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license: creativeml-openrail-m
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base_model: /home/ubuntu/model/stable-diffusion-v1-4
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instance_prompt: a picture of wechat emoji
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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---
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# LoRA DreamBooth - heine123/emoji_out
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These are LoRA adaption weights for /home/ubuntu/model/stable-diffusion-v1-4. The weights were trained on a picture of wechat emoji using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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![img_0](./image_0.png)
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![img_1](./image_1.png)
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